1. Field of the Invention
The present invention relates to a method and apparatus for classifying geological materials using image processing techniques, and more particularly, to a method and apparatus for classifying geological materials including stones, rock samples, and rock surfaces according to type and state by sequentially applying image processing techniques, such as a color space analysis, a granulometry, a texture parameter extraction and a texture statistics extraction, to digital images of the geological materials photographed.
2. Description of the Related Art
Conventional methods of classifying geological materials according to type and state mostly rely on experiential judgments of a few geologists. Since the conventional methods are based on a qualitative, not quantitative, analysis, they have revealed limitations in classifying geological materials. In various fields, image processing techniques are used to objectively and automatically classify target objects. However, techniques for classifying geological materials, such as stones and rocks, using image processing techniques are virtually non-existent.
Most of the conventional classification methods using image processing techniques classify some components within an image. For example, roads and buildings are extracted from a satellite image or defects are found in an image of a semiconductor.
The present invention is fundamentally different from such conventional classification methods in that the present invention aims to classify photographed objects themselves according to type and state, not some components in an image.
There are a number of conventional classification methods, such as a method of classifying cars according to type, which share similar objectives with the present invention. However, such conventional classification methods are also different from the present invention in that some components, such as a car's axes, in the case of the method of classifying cars according to type, are extracted from an image and objects are classified using the extracted components in the conventional classification methods.
As described above, the conventional methods of classifying geological materials according to type and state heavily rely on experiential judgments of a few geologists. Since the conventional classification methods are not based on a quantitative analysis, classification results obtained using the conventional classification methods are not regarded as reliable and objective results. In addition, it is difficult to secure experts in this area, and it is time consuming, and incurs high costs
When geological materials are classified using image processing techniques, it is difficult to extract the shapes of components of an image since geological materials, such as stones, rock samples, and rock surfaces, have non-uniform image characteristics.